← openxiv:cs.AI.2026.00001 · cs.AI
From Validation to Discovery: An Inverse-Docking Experiment for Culturally Calibrated Synthetic Personas Across Five Geographies and Two Population Types
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**Problem Statement:** Synthetic persona platforms are predominantly employed for validation—testing predefined concepts against simulated panels. This work inverts that paradigm, proposing an open-ended discovery use case where culturally calibrated personas generate novel pain themes for subsequent external verification. **Method:** An inverse-docking experiment was conducted across five geographies (India, UAE, Australia, Southeast Asia, Germany) and two population types (B2C consumers, B2B finance/compliance professionals). 1,433 personas produced 212 distinct pain themes via open-ended elicitation, which were then symmetrically validated against venture-market evidence (funded startups and category-forming activity) in each market. **Main Results:** Between 40% and 79% of high-volume themes mapped to currently funded ventures, with validation rates varying by context: India B2C (79%), Germany B2B (58%), and UAE/Australia/Southeast Asia (40–43%). Remaining themes (21–60%) were classified as partial-gap or unowned commercial space. In the Southeast Asian mixed-country study, themes self-stratified by nationality (e.g., Filipino remittance/motorcycle-taxi, Malaysian prayer/Ramadan, Thai banana-leaf/motorbike). Across all studies, personas consistently surfaced pains where incumbents addressed adjacent problem layers rather than the persona-named friction, motivating a *Discovery Index* metric. **Limitations:** Validation rates varied substantially and remained below 80% in most markets, indicating that a significant share of surfaced themes lack current venture coverage. The approach requires independent replication across additional geographies and population types to confirm generalizability, and the boundary between partial-gap and unowned spaces needs tighter operationalization.
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